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Featured researches published by D. A. Cunningham.


Medicine and Science in Sports and Exercise | 1988

Age-related changes in speed of walking

Joan E. Himann; D. A. Cunningham; Peter A. Rechnitzer; Donald H. Paterson

Self-paced walking was used as a measure of the neuromuscular slowing observed with aging. The effects of age on the choice of speed of walking, stride length, and step frequency were described for 289 males and 149 females aged 19 to 102 yr. These subjects were asked to walk at three self-selected paces (slow, normal, and fast) over an 80-m indoor course. Sixty-two years coincided with an accelerated decline in speed of walking. Before 62 yr, there was a 1 to 2% per decade decline in normal walking speed. After 63 yr, females showed a 12.4% per decade decrease and males showed a 16.1% per decade decrease. The eldest group (63 yr and older) had a significantly slower speed of walking and smaller step length than the younger groups (19 to 39 and 40 to 62 yr) for all paces. Heart rate at the three paces was not changed across age. In a multiple regression analysis, the only significant independent variable for walking speed at all three paces was (age), which accounted for 19 to 38% of the variance. When the population was divided into two age ranges (19 to 62 and 63 to 102 yr), walking speed was associated with height before 62 yr and with height and age after 62 yr.


American Journal of Preventive Medicine | 2003

Can primary care doctors prescribe exercise to improve fitness?: The step test exercise prescription (STEP) project

Robert J. Petrella; John J. Koval; D. A. Cunningham; Donald H. Paterson

BACKGROUND Sedentary lifestyle is associated with adverse health outcomes. Available evidence suggests that, despite positive attitudes toward regular exercise in promoting a healthy lifestyle, few physicians actually prescribe exercise for their patients. Barriers include lack of skills and standard office instruments. Because primary care physicians have regular contact with a large proportion of the population, the impact of preventive health interventions may be great. OBJECTIVES To determine the effect of an exercise prescription instrument (i.e., Step Test Exercise Prescription [STEP]), compared to usual-care exercise counseling delivered by primary care doctors on fitness and exercise self-efficacy among elderly community-dwelling patients. DESIGN Randomized controlled trial; baseline assessment and intervention delivery with postintervention follow-up at 3, 6, and 12 months. SETTING Four large (>5000 active patient files) academic, primary care practices: three in urban settings and one in a rural setting, each with four primary care physicians; two clinics provided the STEP intervention and two provided usual care control. PARTICIPANTS A total of 284 healthy community-dwelling patients (72 per clinic) aged >65 years were recruited in 1998-1999. INTERVENTION STEP included exercise counseling and prescription of an exercise training heart rate. MAIN OUTCOME MEASURES The primary outcome measure was aerobic fitness (VO(2max)). Secondary outcomes included predicted VO(2max) from the STEP test, exercise self-efficacy (ESE), and clinical anthropometric parameters. RESULTS A total of 241 subjects (131 intervention, 110 control) completed the trial. VO(2max) was significantly increased in the STEP intervention group (11%; 21.3 to 24ml/kg/min) compared to the control group (4%; 22 to 23ml/kg/min) over 6 months (p <0.001), and 14% (21.3 to 24.9ml/kg/min) and 3% (22.1 to 22.8ml/kg/min), respectively, at 12 months (p <0.001). A similar significant increase in ESE (32%; 4.6 vs 6.8) was observed for the STEP group compared to the control group (22%; 4.2 vs 5.4) at 12 months (p < 0.001). Systolic blood pressure decreased 7.3% and body mass index decreased 7.4% in the STEP group, with no significant change in the control group (p <0.05). Exercise counseling time was significantly (p <0.02) longer in the STEP (11.7+/-3.0 min) compared to the control group (7.1+/-7.0 min), but more (p <0.05) subjects completed > or =80% of available exercise opportunities in the STEP group. CONCLUSIONS Primary care physicians can improve fitness and exercise confidence of their elderly patients using a tailored exercise prescription (e.g., STEP). Further, STEP appears to maintain benefits to 12 months and may improve exercise adherence. Future study should determine the impact of combining cognitive/behavior change strategies with STEP.


Medicine and Science in Sports and Exercise | 1994

Exercise on-transient gas exchange kinetics are slowed as a function of age.

Mark A. Babcock; Donald H. Paterson; D. A. Cunningham; John R. Dickinson

The purpose was to characterize gas exchange kinetics following the on-transient of exercise in men aged 30-80 yr. Forty-six men completed square wave exercise tests from loadless cycling to subventilatory threshold (V(E)T) work rates with gas exchange measured breath-by-breath. Signal averaged data were fit with a monoexponential equation to derive time constants (tau) for gas exchange and ventilation (tau VO2, tau VCO2, tau VE) and heart rate (tau HR). There was a significant slowing of ventilation and gas exchange kinetics across age with linear regression yielding an increase of 0.67 s.yr-1 for tau VO2 (39 s in young to 61 s in old), 0.57 s.yr-1 for tau VCO2, and 0.65 s.yr-1 for tau VE, whereas tau HR (44 to 41 s) was not changed significantly. The slowed VO2 kinetics with age may reflect limitations in muscle blood flow or in control of the rate of oxidative metabolism. The less marked slowing of tau VCO2 compared with tau VO2 across age may reflect reduced CO2 storage capacity with loss of muscle tissue. The tau VE change across age was similar to that for tau VCO2 (tau VE/tau VCO2 unchanged). The present study demonstrated marked age-related slowing of gas exchange dynamics at exercise onset.


European Journal of Applied Physiology | 1983

Energy cost of treadmill and floor walking at self-selected paces

M. E. Pearce; D. A. Cunningham; Allan Donner; Peter A. Rechnitzer; G. M. Fullerton; John H. Howard

SummaryOxygen uptake-velocity regression equations were developed for floor and level treadmill walking by having two groups of men, aged 19–29 years (n=20) and 55–66 years (n=22), walk at four self-selected paces, from “rather slowly” to “as fast as possible”. A two-variable quadratric model relating VO2 (ml·kg−1·min−1) to velocity (m·s−1) was adopted for prediction purposes. However, age and fatness significantly (p<0.05) interacted with treadmill walking speed, while age alone significantly interacted with floor speed. In addition, a significant difference was found between the energy cost of floor and treadmill walking. For example at the normal walking speed of 1.33 m·s−1, the energy cost for the treadmill (age 55–66 years) was 10.58 ml·kg−1·min−1 and for the floor, 11.04 ml·kg−1·min−1 (p<0.05). Four quadratic equations are therefore presented, one each for floor and treadmill in each of the two age-groups. The percent variance explained was between 87 and 95% for each of these equations.


Medicine and Science in Sports and Exercise | 1981

Reasons for dropout from exercise programs in post-coronary patients.

Andrew Gm; Neil Oldridge; Parker Jo; D. A. Cunningham; Peter A. Rechnitzer; N. L. Jones; Buck C; Terence Kavanagh; Roy J. Shephard; Sutton

The dropout rate in the 7-yr Ontario Exercise Heart Collaborative Study of post-coronary men engaged in exercise programs was examined in order to determine possible contributing factors. A questionnaire pertaining to psychosocial and program-related variables was distributed to 728 subjects who were previously assigned randomly on the basis of four prognostic risk factors (occupation, personality, hypertension, and angina) into exercise groups: low intensity exercise (LIE), and high intensity exercise (HIE). Comparisons of answers by the 639 respondents (266 dropouts; 373 compliers) were made initially by chi-square analysis to determine significant categories of questions and, subsequently, by a logistic transform to determine the specific questions which related significantly to the dropout rate. It was found that three main categories were associated with a high dropout rate: convenience aspects of the exercise center, perceptions of the exercise program, and family/lifestyle factors. These three main categories should be carefully considered when designing and implementing potential compliance-improving strategies for secondary prevention exercise programs entailing long-term adherence.


Human Relations | 1977

Work Patterns Associated with Type A Behavior: A Managerial Population

John H. Howard; D. A. Cunningham; Peter A. Rechnitzer

Managers (236) from 12 different companies were examined for the prevalence of Type A behavior. In addition, a number of work habits and job related variables (work hours per week, travel habits, job satisfaction, job tension factors, salary) were obtained on each respondent. Overall, 61% of the managers were classified as Type As, and between companies the percentage varied between 50 and 76%. Type A behavior was also found to be related to recent company growth rates. On work habits, it was found that that extreme Type A s tend to work more hours per week and travel more days per year. It was also found that the Type A s tend to be less satisfied with their jobs. Using factor analysis, fivejobfactors were isolated and these were entitled Ambiguity, Locked-In, Stagnation, Isolation, and Contentment. Type As were found to be different from Type Bs on the factors Locked-In and Contentment. The Locked-In factor is interpreted as reflecting greater self-confidence among the Type As. The Contentment factor reflected job conditions most likely responsible for eliciting Type A behavior. These included: supervisory responsibility for people, a feeling of competition in work, heavy work loads, and conflicting demands. It was also found that Type As earned higher salaries than Type Bs. The results are combined with those of a previous study on the same group of managers, which measured a number of health variables related to Type A behavior and coronary heart disease. A conceptual model is proposed showing the pathways by which susceptible individuals encounter job conditions which elicit Type A behavior and, consequently, higher coronary risk.


Journal of the American Geriatrics Society | 2004

Longitudinal study of determinants of dependence in an elderly population.

Donald H. Paterson; Devin Govindasamy; Marjan Vidmar; D. A. Cunningham; John J. Koval

Objectives: To describe those factors, from the host of initial measures in ambulatory, independent older men and women, that were determinants of becoming dependent over an 8‐year follow‐up.


Medicine and Science in Sports and Exercise | 1994

Effects of aerobic endurance training on gas exchange kinetics of older men

Mark A. Babcock; Donald H. Paterson; D. A. Cunningham

The kinetics of gas exchange at the on-transient of exercise are appreciably slowed in older individuals. Eight older men (72 yr) completed 6 months of aerobic cycle training. Ventilation and gas exchange kinetics were determined at the onset of a below threshold (ventilatory threshold, V(E)T) square wave exercise function and compared with control values (N = 4, age 70 yr). Gas exchange data were measured breath-by-breath and signal averaged data were fit with a monoexponential function to determine the time constants (tau). The training group showed significant increases in VO2max (20%) and VO2 at V(E)T (21%). The tau for oxygen uptake kinetics decreased significantly (62.2 +/- 15.5 to 31.9 +/- 7.0 s). The tau VCO2 (70.9 +/- 10.9 to 43.8 +/- 11.4 s) and tau VE (89.2 +/- 18.0 to 50.4 +/- 11.3) also were significantly faster posttraining; however, tau HR (38.1 +/- 20.5 to 28.6 +/- 7.2) was not significantly altered. Thus, with a vigorous training program, the kinetics of gas exchange of older individuals were faster, and approached values reported in fit young subjects.


Journal of human stress | 1976

Health patterns associated with type A behavior: a managerial population.

John H. Howard; D. A. Cunningham; Peter A. Rechnitzer

Type A Behavior is a behavioral syndrome found to be related to coronary heart disease and characterized by excessive drive, ambition, and competitiveness. Managers from 12 different companies were examined for this syndrome and for a number of the known risk factors in coronary heart disease (blood pressure, cholesterol, triglycerides, uric acid, smoking, and fitness). Those individuals exhibiting extreme Type A Behavior (Type A) showed significantly higher blood pressure (systolic and diastolic) and higher cholesterol and triglyceride levels. A greater percentage of these individuals were cigarette smokers. On serum uric acid there were no differences. In each age group, Type As were less interested in exercise, although differences in cardio-respiratory fitness were found only in the oldest age group. Type A Behavior also was related to age, education, company growth rates, and stress symptoms. Overall, the Type A1s were found to be higher on a number of risk factors known to be associated with coronary heart disease. With regard to the Type A2s (individuals with less developed Type A Behavior), the findings were not conclusive.


American Journal of Cardiology | 1983

Relation of exercise to the recurrence rate of myocardial infarction in men: Ontario exercise-heart collaborative study

Peter A. Rechnitzer; D. A. Cunningham; George M. Andrew; Carol Buck; N. L. Jones; Terence Kavanagh; Neil Oldridge; John O. Parker; Roy J. Shephard; J. R. Sutton; Allan Donner

The Ontario Exercise-Heart Collaborative Study was a multicenter randomized clinical trial of high Intensity exercise for the prevention of recurrent myocardial infarction in men. The 4-year recurrence rate among 379 patients on a program of high intensity exercise did not differ significantly from that among 354 control patients on a program of light exercise, despite the greater reduction in heart rate in the former group. The relative odds of recurrence in the high intensity group were 1.09, with 95% confidence limits of 0.61 and 1.96.

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Donald H. Paterson

University of Western Ontario

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D. H. Paterson

University of Western Ontario

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Peter A. Rechnitzer

University of Western Ontario

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John M. Kowalchuk

University of Western Ontario

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John H. Howard

University of Western Ontario

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Allan Donner

University of Western Ontario

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John J. Koval

University of Western Ontario

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Robert J. Petrella

University of Western Ontario

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Charles L. Rice

University of Western Ontario

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Tom J. Overend

University of Western Ontario

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